Cell counting is a standard, daily procedure in laboratories with numerous application in diagnostics and scientific research. Such an indicator might be helpful in determining the state of cell culture development, bacteria proliferation and pathology detection [1-2]. For instance analysis of blood smear images, based on cell counting, plays a vital role in the field of medicine as it helps to diagnose the disease at the early stage . It provides support for the doctors to take the right decision of monitoring and in result, prevention of the disease.
After acquiring image from microscope is necessary to define number of cells . Usually, a hemocytometer is used to perform this task. This method, however, has many disadvantages and it's likely to be inaccurate, due to limited counting area. Farther, intersections of lines heavily contribute to false positives . Moreover, the manual counting is tedious likewise time-consuming [3-5]. It also puts under stress medical laboratory technicians which has an influence on erroneous results. A commercial cell counter may provide considerable improvement, but the cost of the instrument and consumables are high .
Automatic operations using sophisticated algorithms allows to solve those problems. First, the area captured by the camera is larger than the suggested areas for manual cell counting, thus encompassing a larger cell population. It also helps to avoid a problem with different cell density in observed field . It is proved that this approach demonstrates a key advantage of consistency, as well as simplicity, accuracy, and speed, and poses an important question with regard to the reliability of manual cell counting at low cell concentrations .
 Özkan A., İşgör S. B., Tora H., Uyar P. and İşcan M.:"An alternative method for cell counting," 2011 IEEE 19th Signal Processing and Communications Applications Conference (SIU), Antalya, 2011,pp.1048-1051.
 Shapiro MF., Greenfield S.: „Diagnostic Decision: The Complete Blood Count and Leukocyte Differential Count: An Approach to Their Rational Application.” Ann Intern Med.; 106:65–74. doi: 10.7326/0003-4819-106-1-65
 Tulsani H., Gupta R. and Kapoor R.: "An improved methodology for blood cell counting", IMPACT-2013, Aligarh, 2013, pp. 88-92.
 Grishagin I. V.: „Automatic cell counting with ImageJ”, Analytical Biochemistry, Volume 473, 2015, Pages 63-65
 Sizto N. L., Dietz L. J.: „Method and apparatus for cell counting and cell classification”, US patent 5,556,764, Sep. 17, 1996
 Acharya, V., & Kumar, P. (2017). Identification and red blood cell automated counting from blood smear images using computer-aided system. Medical & Biological Engineering & Computing, 56(3), 483–489. doi:10.1007/s11517-017-1708-9